Kimi K2.5/K2.6 1T — B200 vs MI325X Performance per Dollar
Cost per million tokens of B200 (NVIDIA Blackwell) versus MI325X (AMD CDNA 3) on Kimi K2.5/K2.6 1T. Owning-hyperscaler TCO normalized by output tokens — performance per dollar across LLM workloads. Pick the more cost-efficient SKU at every target interactivity level. Use the chart controls below to switch sequences, precisions, and metrics — same interactions as the main inference chart.
B200 edges MI325X at 41 tok/s/user on Kimi K2.5/K2.6 1T — $1.00 per million tokens versus $4.26, a 324% cost-per-token gap.
Push Kimi K2.5/K2.6 1T to 44 tok/s/user and B200 lands at $1.08 per million tokens against MI325X's $4.99 — B200 pulls ahead by 363%.
B200: $1.18 per million tokens. MI325X: $6.10. Both at 48 tok/s/user on Kimi K2.5/K2.6 1T, with B200 416% cheaper. (Numbers reflect the default 1k/1k · int4 selection for this URL — table and chart below update if you change sequence, precision, or model in the controls.)
GPU pricing (owning hyperscaler): B200 $1.95/GPU/hr · MI325X $1.28/GPU/hr. Source: SemiAnalysis Market August 2025 Pricing Surveys & AI Cloud TCO Model.
| Metric | Interactivity (tok/s/user) | Interactivity (tok/s/user) | Interactivity (tok/s/user) |
|---|---|---|---|
| Dollar per Million Tokens | B200:$1.003MI325X:$4.259 | B200:$1.077MI325X:$4.986 | B200:$1.183MI325X:$6.102 |
| Concurrency | B200:~56MI325X:~8 | B200:~49MI325X:~7 | B200:~40MI325X:~5 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.